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Interpretable machine learning (R/Python)

Základní info

Popis kurzu

Random forests, ensemble methods and deep neural networks provide powerful prediction methods. However, they are less transparent as a simpler model, like logistic regression or decision trees. This is a challenge for data scientists, specially with regards to increasing regulation, like GDPR. In this course we cover some of the methods that shed light on the black boxes.


Random forests, ensemble methods and deep neural networks provide powerful prediction methods. However, they are less transparent as a simpler model, like logistic regression or decision trees. This is a challenge for data scientists, specially with regards to increasing regulation, like GDPR. In this course we cover some of the methods that shed light on the black boxes.

Určeno pro

Marketing specialists, financial analysts, data analysts and data scientists.

Obsah kurzu


  • Interpreting ensemble models: Random forests, gradient boosting machines.

  • DALEX, LIME and visualization tools (ALE, PDP).

  • Interpreting individual predictions.

Předpoklady

Basic familiarity with data manipulation (for instance, spreadsheet software).

Studijní materiály

V angličtině

Interpretable machine learning (R/Python)

Vybraný termín:

14.4.2021  ONLINE

Cena

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